Listening to Sorting Algorithms! скачать в хорошем качестве

Listening to Sorting Algorithms!

!IMPORTANT NOTE! "Bounce Sort" is actually called "Cocktail Shaker Sort". If anyone is calling it Bounce Sort these days, it's probably my fault. Sorry for that! If you go around calling it Bounce Sort, your professor's gonna be like "wtf is that? F!" and that ain't gonna be fun! Ditto for Banshee Sort, it's probably a type of Bucket Sort! As for Insertion Sort, it's been brought to my attention that it might actually be something called Gnome Sort. Reading about the two at a glance, I think I need to read more. Until then, perhaps you should, too, if it interests you?   ------- Sorting Algorithms used (some were misnamed in the video): 00:00 [1] Bubble sort 00:21 [2] Cocktail Shaker Sort 01:16 [3] Insertion Sort 01:53 [4] Quick Sort 03:07 [5] Bucket Sort, 2 buckets 06:03 [6] Bucket Sort, 10 buckets 08:10 [7] Binary Radix Sort, Least Significant Digit 09:24 [8] Decimal Radix Sort, Least Significant Digit 10:07 [9] Base 121 Radix Sort, Least Significant Digit 10:39 [10] Dynamic Range Random Sort 12:14 [11] Bucket Sort, 192 Buckets 13:09 [12] Racing all together with same data set 13:43 [13] Decimal Radix Sort, Least Significant Digit, finishes 13:51 [14] Quick Sort, finishes 15:08 [15] Bucket Sort, 10 buckets, finishes 15:11 [16] Insertion Sort, finishes 16:19 [17] Cocktail Shaker Sort, finishes 16:50 [18] Dynamic Range Random Sort, finishes 17:07 [19] Bubble Sort, finishes 9000:01 [lol] BOGO sort, still not done - - - - - - - Dynamic Range Random Sort has 2 phases and a 'Tries counter'. Phase 1: It randomly selects two elements in the list, a left element and right element. If right has a smaller value than left, they are swapped, and reset Tries to 0. Else, no swap, and we increment Tries by 1. If Tries becomes larger than some number (say 30 for example), it enters phase 2. Phase 2: Randomly select one element in the list, then randomly select either the element to the left or the right of that. If the two elements are in descending order, swap them and reset Tries to 0. Else, increment Tries by 1. If Tries ever becomes larger than some number, (such as 30 for example), verify that the list is sorted. If it is, we're done! If not, reset Tries to 0 and resume phase 2. This sorting algorithm can take a very disorganized list and quickly get it to an almost solved state; each element is very close to where it should be if the list were sorted. But the closer it gets to being solved, the slower it works (each element takes longer to get closer to its correct position)